Decision Tree Classification of Rule-Based MSME Sector Labels for Widowed and Divorced Women Using Socioeconomic Factors

Rahmatsyah Ananta Putra Ginting; Rakhmat Kurniawan

doi:10.55537/j-ibm.v6i1.1820

Authors

Rahmatsyah Ananta Putra Ginting Universitas Islam Negeri Sumatera Utara
Rakhmat Kurniawan Universitas Islam Negeri Sumatera Utara

DOI:

https://doi.org/10.55537/j-ibm.v6i1.1820

Keywords:

decision tree, rule-based labels, socioeconomic factors, MSME sector screening, widowed and divorced women

Abstract

Widowed and divorced women may rely on micro, small, and medium enterprises to sustain household income, yet preliminary sector screening requires a consistent and transparent mechanism. This study developed a Decision Tree model to classify three rule-based MSME sector labels using demographic and economic characteristics. The dataset comprised 3,659 women aged 18–59 years in Kabanjahe District, Karo Regency, Indonesia. Age, occupation, marital-status category, monthly income, number of dependents, and business-ownership status were used as predictors. The target labels—culinary, fashion and handicrafts, and services and creative products—were constructed from predefined weighting rules. After preprocessing and a stratified 80:20 split, evaluation on 732 test records yielded 94.81% accuracy, 94.86% weighted precision, 94.81% weighted recall, and a 94.75% weighted F1-score. Low-income status had the highest impurity-based feature importance (43.11%), followed by the 18–25 age category (12.05%). The model consistently reproduced the constructed labels and produced interpretable decision rules. However, the results do not establish real-world sector suitability or business success because the labels were generated from the same predictor attributes rather than independent expert judgments or observed business outcomes.

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